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Vibe coding your MVP with tools like Cursor or Bolt.new can get your product running fast, but that speed hides serious risks. AI generated code vulnerabilities often slip in because these models focus on "working" code, not secure code. From exposed API keys to broken authentication, the difference between "it runs" and "it's production-ready" could cost you dearly. Let's unpack the vibe coding security risks you need to know before launch or fundraising.
Vibe coding refers to the practice of using AI-powered development tools like Cursor, Bolt.new, v0, or Replit Agent to generate entire applications from simple prompts. This approach has gained popularity among non-technical founders and indie developers who need to build MVPs quickly without extensive coding knowledge.
AI coding assistants are trained to make code that works, not code that's secure. These models aim to satisfy your prompt by creating something functional, but they often miss critical security best practices that human developers learn through experience and training.
One of the most frequent vibe coding security risks involves improper handling of sensitive information. AI tools regularly embed API keys directly in code rather than using environment variables or secure storage solutions. This practice can lead to credential leaks when code is pushed to public repositories.
AI-generated database interactions frequently lack proper input sanitisation. Without proper validation, user inputs can be manipulated to execute unauthorised database commands, potentially exposing or destroying your data.
Many AI tools create authentication systems that appear functional but contain serious flaws. Common issues include:
AI-generated endpoints often fail to verify that users have permission to access requested resources. This oversight allows attackers to manipulate references to access unauthorised data.
Bolt.new security concerns frequently include a lack of rate limiting on authentication endpoints, making brute force attacks trivial. Similarly, cursor security issues often involve unprotected API endpoints that can be abused for denial-of-service attacks.
There's an enormous gap between code that functions in a demo and code that's ready for real users. AI generated code vulnerabilities create technical debt that compounds over time, making your application increasingly difficult to secure as it grows.
Security researchers have identified consistent patterns in AI-generated applications:
The initial speed advantage of vibe coding diminishes quickly when security issues emerge. Fixing security problems after deployment is typically 30-100 times more expensive than addressing them during development.
Before pitching to investors or launching to users, invest in a professional security assessment. An experienced security team can identify vulnerabilities that AI tools miss and provide actionable recommendations for remediation.
Integrate basic security testing into your development process:
Vibe coding can still be valuable for prototyping, but recognise its limitations. Use AI tools to generate initial code, then apply human expertise to review and secure that code before deployment.
The promise of rapid development through AI coding tools is appealing, but the hidden security costs can be substantial. By understanding these risks and implementing appropriate safeguards, you can enjoy the benefits of vibe coding without compromising the security of your product and the trust of your users.
For founders preparing for launch or fundraising, a security-first approach demonstrates maturity and responsibility that investors value. Consider a professional security review of your AI-built MVP to identify and address potential vulnerabilities before they become costly problems.
